Unless otherwise indicated herein, the approaches described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
The present invention relates to the analysis of business data, and in particular to improved techniques for customized presentation and consumption of visual analytic data. In the course of conducting business, many entities (e.g., businesses) generate large amounts of data. To help make sense of such vast amounts of data, many business systems use business systems that rely on integrated and add-on analytical tools to analyze, summarize, or otherwise process the data. For example, a typical business system may include a number of databases containing large stores of business data on which an analytical engine can execute various analytical operations. The specifications and order of the analytical operations can be designed to generate specific analytical data for a particular purpose or use. For instance, a manufacturing manager may use the analytical engine in an accounting system to aggregate costs from many invoices for components that are used to produce end products to calculate the total component cost of the end products. The resulting analytical data (e.g., the total component costs for various end products) can be compiled into an analysis report according to a particular report definition. The report definition may specify any number of analytical operations to produce analytical data with specific dimensions that are presented in a specific analysis report format (e.g., level of granularity, time period, specific product groups/types presented in a tabular form). For example, a report definition may specify that the aggregation of the costs from the invoices be performed on a weekly, monthly, annual, or other periodic basis for individual end products or groups/families of end products, and presented in specific file format (e.g., a spreadsheet with specific column names) based on the needs or purposes of the manufacturing manager.
While the resulting analysis reports may be useful to the intended end users (e.g., business users), the typical intended end user is not usually capable or interested in defining the report definition (i.e., designing and programming the necessary backend analytical operations) that generates the report. In general, specialized users with a high level of technical expertise and understanding of the underlying data structures are responsible for designing and implementing report definitions. These users are often referred to as “technical users”.
Technical users are usually adept, not only at defining and implementing report definitions, but also at interpreting and understanding the resulting reports. However, most end users of business systems are not technical users and, therefore, do not usually have the level of technical expertise necessary to easily understand the resulting reports, let alone define and implement analytical operations to create their own report definitions. To the average business user, most analysis reports look like a table of meaningless numbers that are difficult to consume or summarize. To increase the usability of analysis reports, various techniques have been developed to present the analytical data in the reports to non-technical users in more easily understandable formats.
For example, some business systems execute predetermined report definitions (e.g., collections of individual and interrelated analytical operations) on the underlying data to generate analytical data that can ultimately be represented in one or more visual analytics (e.g., charts, graphs, tables, etc.) that are easily understandable by non-technical users. Such predetermined reports definitions and the visual analytics are usually designed by a technical user with a particular purpose or mode of consumption in mind. Based on individual needs, non-technical users, who are often referred to herein as “business users”, can select the predetermined report definitions and visual analytics to be included in customized or personalized user interface (UI) portals commonly referred to as “dashboards”.
Such dashboards often include graphical user interfaces (GUIs) that present business users with selections of compact and succinct representations of the visual analytics within an organized framework (e.g., a grid of framed visual analytics having to do with specific aspects of a business or venture) that are of particular pertinence to the tasks and responsibilities of the associated business user. For instance, a manufacturing engineer may be interested in the logistics of a supply chain for a particular product line and/or the available manufacturing resources within the company for resource planning purposes. In such scenarios, the manufacturing engineer may select a particular report definition that when applied to the appropriate business data will generate a report that represents forecasted production capabilities of one or more component manufacturers. The manufacturing engineer can also select and apply a number of predetermined visual analytic patterns (i.e., instructions for generating one or more visual analytics) that the business system can apply to the analytical data in the report to generate specific visual analytics. For example, the manufacturing engineer may select a visual analytic pattern that, when applied to the appropriate analytical data/analysis report, causes the business system to render a labeled line graph of projected supplier factory outputs, or a stacked bar graph that shows total versus available internal production capacities with percentile labels. The resulting visual analytics are then displayed to the manufacturing engineer (i.e., the intended end user) in a home page of his portal or client application that accesses the business system.